SoroushVahidi/scidocs huggingface dataset:
Interaction as performance : cases of configuring physical interfaces in mixed media
(2004)

Mixed media, as artful assemblages of digital objects and physical artefacts, provide distinctive opportunities for experiential, presentational and representational interaction. In project-based learning of architecture design, participants staged spatial narratives with multiple projections, performed mixed objects and artefacts, and exploited bodily movements in mixed representations. These cases show how physical interfaces in mixed media acquire a spatial dimension, integrate physical artefacts and bodily movements and propose configurability as a central feature. A perspective based on anthropological concepts of performance makes it possible to address these aspects in a coherent way, pointing to sense experience, the individuality and collective emergence of expression and its diachronic and event-like character. From this perspective, interaction is part of expressive events aimed at generating new insights for participants (interchangeable performers and spectators) privileging sense experience. Events are the outcome of configurations of space, artefacts and digital media, and are characterised by a simultaneousness of doing and undergoing, of bodily presence and representation. More importantly, the performance perspective suggests a particular temporal view of interaction, based on the concept of event, addressing a neglected granularity of analysis between the moment-by-moment unfolding of interaction and the longer term co-evolution of technology and practice. Implications of interaction as performance contribute to a wider program of interaction design, thereby providing alternatives to established human-computer interaction tenets: the notion of event is an alternative to the notion of task; perception in Dewey's terms replaces recognition proposing expression as an alternative to accountability and usability. Implications include looking at how space can be configured and staged instead of measured or simulated, and how situations can be staged instead of sensed and recognised, privileging the sensing human over the
Driver Gaze Region Estimation Without Using Eye Movement
(2015)

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Controlling privacy in recommender systems
(2014)

Recommender systems involve an inherent trade-off between accuracy of recommendations and the extent to which users are willing to release information about their preferences. In this paper, we explore a two-tiered notion of privacy where there is a small set of “public” users who are willing to share their preferences openly, and a large set of “private” users who require privacy guarantees. We show theoretically and demonstrate empirically that a moderate number of public users with no access to private user information already suffices for reasonable accuracy. Moreover, we introduce a new privacy concept for gleaning relational information from private users while maintaining a first order deniability. We demonstrate gains from controlled access to private user preferences.
On fast surface reconstruction methods for large and noisy point clouds
(2009)

In this paper we present a method for fast surface reconstruction from large noisy datasets. Given an unorganized 3D point cloud, our algorithm recreates the underlying surface's geometrical properties using data resampling and a robust triangulation algorithm in near realtime. For resulting smooth surfaces, the data is resampled with variable densities according to previously estimated surface curvatures. Incremental scans are easily incorporated into an existing surface mesh, by determining the respective overlapping area and reconstructing only the updated part of the surface mesh. The proposed framework is flexible enough to be integrated with additional point label information, where groups of points sharing the same label are clustered together and can be reconstructed separately, thus allowing fast updates via triangular mesh decoupling. To validate our approach, we present results obtained from laser scans acquired in both indoor and outdoor environments.
Distant Supervision for Relation Extraction with Hierarchical Attention and Entity Descriptions
(2018)

Distant supervision for relation extraction is an effective method to find novel relational facts from plain text. However, distant supervision inevitably suffers from wrong label problem, and most existing methods generally focus on direct sentences containing entity pairs, but ignore massive information from background knowledge. To tackle these problems, we propose a novel hierarchical attention model to select valid instances and capture vital semantic information in them. Furthermore, we incorporate entity descriptions extracted from Wikipedia into the hierarchical attention model to provide supplementary background knowledge. The proposed architecture can not only combat the noise introduced by distant supervision, but also adequately extract latent and helpful background information. The experimental results on both Chinese and English datasets show that the proposed approach consistently achieves significant improvements on relation extraction as compared with strong baselines.
2018 Low-Power Image Recognition Challenge
(2018)

The Low-Power Image Recognition Challenge (LPIRC, ​https://rebootingcomputing.ieee.org/lpirc​) is an annual competition started in 2015. The competition identifies the best technologies that can classify and detect objects in images efficiently (short execution time and low energy consumption) and accurately (high precision). Over the four years, the winners’ scores have improved more than 24 times. As computer vision is widely used in many battery-powered systems (such as drones and mobile phones), the need for low-power computer vision will become increasingly important. This paper summarizes LPIRC 2018 by describing the three different tracks and the winners’ solutions.
A layered naming architecture for the internet
(2004)

Currently the Internet has only one level of name resolution, DNS, which converts user-level domain names into IP addresses. In this paper we borrow liberally from the literature to argue that there should be three levels of name resolution: from user-level descriptors to service identifiers; from service identifiers to endpoint identifiers; and from endpoint identifiers to IP addresses. These additional levels of naming and resolution (1) allow services and data to be first class Internet objects (in that they can be directly and persistently named), (2) seamlessly accommodate mobility and multi-homing and (3) integrate middleboxes (such as NATs and firewalls) into the Internet architecture. We further argue that flat names are a natural choice for the service and endpoint identifiers. Hence, this architecture requires scalable resolution of flat names, a capability that distributed hash tables (DHTs) can provide.
Pathophysiology of human visceral obesity: an update.
(2013)

Excess intra-abdominal adipose tissue accumulation, often termed visceral obesity, is part of a phenotype including dysfunctional subcutaneous adipose tissue expansion and ectopic triglyceride storage closely related to clustering cardiometabolic risk factors. Hypertriglyceridemia; increased free fatty acid availability; adipose tissue release of proinflammatory cytokines; liver insulin resistance and inflammation; increased liver VLDL synthesis and secretion; reduced clearance of triglyceride-rich lipoproteins; presence of small, dense LDL particles; and reduced HDL cholesterol levels are among the many metabolic alterations closely related to this condition. Age, gender, genetics, and ethnicity are broad etiological factors contributing to variation in visceral adipose tissue accumulation. Specific mechanisms responsible for proportionally increased visceral fat storage when facing positive energy balance and weight gain may involve sex hormones, local cortisol production in abdominal adipose tissues, endocannabinoids, growth hormone, and dietary fructose. Physiological characteristics of abdominal adipose tissues such as adipocyte size and number, lipolytic responsiveness, lipid storage capacity, and inflammatory cytokine production are significant correlates and even possible determinants of the increased cardiometabolic risk associated with visceral obesity. Thiazolidinediones, estrogen replacement in postmenopausal women, and testosterone replacement in androgen-deficient men have been shown to favorably modulate body fat distribution and cardiometabolic risk to various degrees. However, some of these therapies must now be considered in the context of their serious side effects. Lifestyle interventions leading to weight loss generally induce preferential mobilization of visceral fat. In clinical practice, measuring waist circumference in addition to the body mass index could be helpful for the identification and management of a subgroup of overweight or obese patients at high cardiometabolic risk.
Linked Data and multimedia: the state of affairs
(2011)

Linked Data is a way of exposing and sharing data as resources on the Web and interlinking them with semantically related resources. In the last three years significant amounts of data have been generated, increasingly forming a globally connected, distributed data space. For multimedia content, metadata are a key factor for efficient management, organization, and retrieval. However, the relationship between multimedia and Linked Data has been rarely studied, leading to a lack of mutual awareness and, as a consequence thereof, technological deficiencies. This article introduces the basic concepts of Linked Data in the context of multimedia metadata, and discusses techniques to generate, expose, discover, and consume Linked Data. It shows that a large amount of data sources exist, which are ready to be exploited by multimedia applications. The benefit of Linked Data in two multimedia-related applications is discussed and open research issues are outlined with the goal of bringing the research fields of multimedia and Linked Data closer together in order to facilitate mutual benefit.
Cheek defects.
(2009)

The challenge surgeons face when reconstructing cheek defects varies significantly depending on the location and depth of the defect and the distensibility of the surrounding tissues. The cheek is a large aesthetic unit characterized in most areas with a convex surface and inherent transitions in color and texture. These characteristics demand the surgeon's attention to achieve superior results during reconstruction. Surgeons must also recognize the free margins of the adjacent structures, including the lower eyelid, nasal ala, and lip, to minimize distortion of these areas during healing. With these challenges in mind, this article discusses several approaches to reconstruction of various types of cheek defects.
Role of self-care in management of diabetes mellitus
(2013)

Diabetes mellitus (DM) is a chronic progressive metabolic disorder characterized by hyperglycemia mainly due to absolute (Type 1 DM) or relative (Type 2 DM) deficiency of insulin hormone. World Health Organization estimates that more than 346 million people worldwide have DM. This number is likely to more than double by 2030 without any intervention. The needs of diabetic patients are not only limited to adequate glycemic control but also correspond with preventing complications; disability limitation and rehabilitation. There are seven essential self-care behaviors in people with diabetes which predict good outcomes namely healthy eating, being physically active, monitoring of blood sugar, compliant with medications, good problem-solving skills, healthy coping skills and risk-reduction behaviors. All these seven behaviors have been found to be positively correlated with good glycemic control, reduction of complications and improvement in quality of life. Individuals with diabetes have been shown to make a dramatic impact on the progression and development of their disease by participating in their own care. Despite this fact, compliance or adherence to these activities has been found to be low, especially when looking at long-term changes. Though multiple demographic, socio-economic and social support factors can be considered as positive contributors in facilitating self-care activities in diabetic patients, role of clinicians in promoting self-care is vital and has to be emphasized. Realizing the multi-faceted nature of the problem, a systematic, multi-pronged and an integrated approach is required for promoting self-care practices among diabetic patients to avert any long-term complications.
Improving the Accuracy and Speed of Support Vector Machines
(1996)

Bernhard Scholkopf" Max-Planck-Institut fur biologische Kybernetik , Spemannstr. 38 72076 Tubingen, Germany bs@mpik-tueb.mpg.de Support Vector Learning Machines (SVM) are finding application in pattern recognition , regression estimation , and operator inversion for ill-posed problems. Against this very general backdrop , any methods for improving the generalization performance, or for improving the speed in test phase, of SVMs are of increasing interest. In this paper we combine two such techniques on a pattern recognition problem. The method for improving generalization performance (the "virtual support vector" method) does so by incorporating known invariances of the problem. This method achieves a drop in the error rate on 10,000 NIST test digit images of 1.4% to 1.0%. The method for improving the speed (the "reduced set" method) does so by approximating the support vector decision surface. We apply this method to achieve a factor of fifty speedup in test phase over the virtual support vector machine. The combined approach yields a machine which is both 22 times faster than the original machine, and which has better generalization performance, achieving 1.1 % error. The virtual support vector method is applicable to any SVM problem with known invariances. The reduced set method is applicable to any support vector machine.
Online continuous stereo extrinsic parameter estimation
(2012)

Stereo visual odometry and dense scene reconstruction depend critically on accurate calibration of the extrinsic (relative) stereo camera poses. We present an algorithm for continuous, online stereo extrinsic re-calibration operating only on sparse stereo correspondences on a per-frame basis. We obtain the 5 degree of freedom extrinsic pose for each frame, with a fixed baseline, making it possible to model time-dependent variations. The initial extrinsic estimates are found by minimizing epipolar errors, and are refined via a Kalman Filter (KF). Observation covariances are derived from the Cramer-Rao lower bound of the solution uncertainty. The algorithm operates at frame rate with unoptimized Matlab code with over 1000 correspondences per frame. We validate its performance using a variety of real stereo datasets and simulations.
ActiveStereoNet: End-to-End Self-supervised Learning for Active Stereo Systems
(2018)

In this paper we present ActiveStereoNet, the first deep learning solution for active stereo systems. Due to the lack of ground truth, our method is fully self-supervised, yet it produces precise depth with a subpixel precision of 1/30th of a pixel; it does not suffer from the common over-smoothing issues; it preserves the edges; and it explicitly handles occlusions. We introduce a novel reconstruction loss that is more robust to noise and texture-less patches, and is invariant to illumination changes. The proposed loss is optimized using a window-based cost aggregation with an adaptive support weight scheme. This cost aggregation is edge-preserving and smooths the loss function, which is key to allow the network to reach compelling results. Finally we show how the task of predicting invalid regions, such as occlusions, can be trained end-toend without ground-truth. This component is crucial to reduce blur and particularly improves predictions along depth discontinuities. Extensive quantitatively and qualitatively evaluations on real and synthetic data demonstrate state of the art results in many challenging scenes.
The internet of energy: a web-enabled smart grid system
(2012)

The quest for sustainable energy models is the main factor driving research on smart grid technology. SGs represent the bridging paradigm to enable highly efficient energy production, transport, and consumption along the whole chain, from the source to the user. Although this concept promises to be very fruitful, the research on how to deploy it in the real world has just begun. A discussion on the enabling technologies for SGs and a possible roadmap for the profitable evolution thereof is the focus of this article. After introducing the recent trends that are pushing the SG paradigm, we will discuss various key scenarios for the SG, and briefly introduce some of its key requirements. We will then provide an analysis of how current and future standard solutions in the areas of communications and networking can be engineered into a system that fulfills the needs of the SG vision. We advocate the use of small, cheap, and resource-constrained devices with pervasive computing capabilities as the key component to deploy a ubiquitous energy control system. To this end, the recent efforts carried out by Internet standardization bodies such as the IETF and W3C toward the vision of the Internet of Things (IoT) are especially relevant. The various components of the proposed solution have been successfully showcased in real-world implementations, and relevant actors such as ETSI, ZigBee, and IPSO are already evaluating their potential for future IoT applications, making the Internet-based smart grid vision considered in this article practically achievable in the not too distant future.
Power laws , Pareto distributions and Zipf ’ s law
(2004)

When the probability of measuring a particular value of some quantity varies inversely as a power of that value, the quantity is said to follow a power law, also known variously as Zipf’s law or the Pareto distribution. Power laws appear widely in physics, biology, earth and planetary sciences, economics and finance, computer science, demography and the social sciences. For instance, the distributions of the sizes of cities, earthquakes, forest fires, solar flares, moon craters and people’s personal fortunes all appear to follow power laws. The origin of power-law behaviour has been a topic of debate in the scientific community for more than a century. Here we review some of the empirical evidence for the existence of power-law forms and the theories proposed to explain them.
LED driver circuit with inherent PFC
(2010)

A buck-boost topology operating in discontinuous conduction mode (DCM) is used as an off line LED driver for lighting applications. Operating from a full wave rectified ac-voltage with minimum input capacitance, with a constant switching frequency and constant on-time, the utility current has near unity power factor. This LED driver is suitable for cost sensitive applications because this circuit has a minimal parts count and a very simple control circuit. Disadvantages are that the LED drive current is modulated at twice the utility frequency and DCM operation increases component stress levels.
Retargeting Semantically-Rich Photos
(2015)

Semantically-rich photos contain a rich variety of semantic objects (e.g., pedestrians and bicycles). Retargeting these photos is a challenging task since each semantic object has fixed geometric characteristics. Shrinking these objects simultaneously during retargeting is prone to distortion. In this paper, we propose to retarget semantically-rich photos by detecting photo semantics from image tags, which are predicted by a multi-label SVM. The key technique is a generative model termed latent stability discovery (LSD). It can robustly localize various semantic objects in a photo by making use of the predicted noisy image tags. Based on LSD, a feature fusion algorithm is proposed to detect salient regions at both the low-level and high-level. These salient regions are linked into a path sequentially to simulate human visual perception . Finally, we learn the prior distribution of such paths from aesthetically pleasing training photos. The prior enforces the path of a retargeted photo to be maximally similar to those from the training photos. In the experiment, we collect 217 1600 ×1200 photos, each containing over seven salient objects. Comprehensive user studies demonstrate the competitiveness of our method.
Euler Number and Connectivity Indexes of a Three Dimensional Digital Picture
(2003)

Fundamental properties of topological structure of a 3D digitized picture are presented including the concept of neighborhood and connectivity among volume cells (voxels) of 3D digitized binary pictures defined on a cubic grid, the concept of simplicial decomposition of a 3D digitized object, and two algorithms for calculating the Euler number (genus). First we define four types of connectivity. Second we present two algorithms to calculate the Euler number of a 3D figure. Thirdly we introduce new local features called the connectivity number (CN) and the connectivity index to study topological properties of a 3D object in a 3D digitized picture. The CN at a 1-voxel (=a voxel with the value 1) x is defined as the change in the Euler number of the object caused by changing the value of x into zero, that is, caused by deleting x. Finally, by using them, we prove a necessary and sufficient condition that a 1-voxel is deletable. A 1-voxel x is said to be deletable if deletion of x causes no decrease and no increase in the numbers of connected components, holes and cavities in a given 3D picture.